Plots
Correlogram
Trend pattern (correlogram 1 : less correlation with increasing
lags),
Seasonal pattern (correlogram 2 : correlation (highest value at lag
52/53) and anti-correlation (lowest value at lag 26/27)
successions),
Periodicity = 52 (highest correlation value at 52/53)
Trend and seasonal patterns identification :
Time series = Tt + St + ɛt
with Tt : trend St : seasonal pattern ɛt : residual part
Quick overview of the components of the series
increasing trend more visible
→ measured values - seasonal pattern
OR
→ trend + remainders
by appling trend on this series, we see the increase
slope : 0.058 ± 0.009
Int. : -98.07 ± 18.57
##
## Call:
## lm(formula = y ~ x, data = reg_val_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.3589 -0.7228 -0.1046 0.7712 4.6640
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -98.074067 18.572196 -5.281 1.64e-07 ***
## x 0.058022 0.009217 6.295 4.97e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.228 on 830 degrees of freedom
## Multiple R-squared: 0.04557, Adjusted R-squared: 0.04442
## F-statistic: 39.63 on 1 and 830 DF, p-value: 4.971e-10
## tau slope intercept
## 0.15799741 0.04960769 -65.78843542
If residuals of the time series are assimilated to a white noise =
stationary time series
Stationary time series = no trend + no seasonality
##
## Box-Ljung test
##
## data: ts_temp_decomp$random
## X-squared = 356.08, df = 1, p-value < 2.2e-16
significative p-value, so we reject that residuals could be associated to a white noise
##
## Call:
## lm(formula = y ~ x, data = reg_val_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.3589 -0.7228 -0.1046 0.7712 4.6640
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -98.074067 18.572196 -5.281 1.64e-07 ***
## x 0.058022 0.009217 6.295 4.97e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.228 on 830 degrees of freedom
## Multiple R-squared: 0.04557, Adjusted R-squared: 0.04442
## F-statistic: 39.63 on 1 and 830 DF, p-value: 4.971e-10
##
## Call:
## lm(formula = reg_val_less_season$y ~ reg_val_less_season$x, data = reg_val_less_season,
## weights = weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -4.6580 -0.7725 -0.1122 0.8246 5.0327
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -97.539344 18.569373 -5.253 1.91e-07 ***
## reg_val_less_season$x 0.057757 0.009216 6.267 5.90e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.315 on 830 degrees of freedom
## Multiple R-squared: 0.04518, Adjusted R-squared: 0.04403
## F-statistic: 39.28 on 1 and 830 DF, p-value: 5.904e-10
## Slope SE Slope P Slope Intercept SE int.
## pco2_therm_ano 1.192733 0.1803486 6.769806e-11 -2403.182 363.3769
## pco2_nontherm_ano 3.643118 0.1380448 1.473270e-111 -7340.347 278.1407
## P int. F df R2 P value
## pco2_therm_ano 6.770535e-11 43.73819 819 0.05069694 6.769806e-11
## pco2_nontherm_ano 1.474678e-111 696.47601 819 0.45957574 1.473270e-111
→ remove seasonality :
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2_therm_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -102.50 -72.44 -21.02 70.23 185.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3077.8957 1217.2320 -2.529 0.01164 *
## x 1.7347 0.6041 2.871 0.00419 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 78.61 on 817 degrees of freedom
## Multiple R-squared: 0.009991, Adjusted R-squared: 0.008779
## F-statistic: 8.245 on 1 and 817 DF, p-value: 0.004193
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2_nontherm_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -87.902 -26.116 -0.017 23.768 101.606
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6630.2703 479.2587 -13.83 <2e-16 ***
## x 3.4929 0.2379 14.69 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 30.95 on 817 degrees of freedom
## Multiple R-squared: 0.2088, Adjusted R-squared: 0.2079
## F-statistic: 215.6 on 1 and 817 DF, p-value: < 2.2e-16
## Slope SE Slope P Slope Intercept SE int.
## pco2_therm_ano 0.3672177 0.1287162 4.441030e-03 -739.8897 259.3448
## pco2_nontherm_ano 3.1254201 0.1394037 3.519009e-87 -6297.2619 280.8787
## P int. F df R2 P value
## pco2_therm_ano 4.441130e-03 8.139187 819 0.009840166 4.441030e-03
## pco2_nontherm_ano 3.521795e-87 502.652819 819 0.380321376 3.519009e-87
→ remove seasonality :
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2_therm_less_season_prof)
##
## Residuals:
## Min 1Q Median 3Q Max
## -42.139 -19.240 -7.184 8.489 174.231
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -455.4318 440.5243 -1.034 0.3015
## x 0.4091 0.2186 1.871 0.0617 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.45 on 817 degrees of freedom
## Multiple R-squared: 0.004267, Adjusted R-squared: 0.003048
## F-statistic: 3.501 on 1 and 817 DF, p-value: 0.06169
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2_nontherm_less_season_prof)
##
## Residuals:
## Min 1Q Median 3Q Max
## -81.616 -14.527 2.456 15.522 78.459
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5880.9327 369.4817 -15.92 <2e-16 ***
## x 3.1015 0.1834 16.91 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 23.86 on 817 degrees of freedom
## Multiple R-squared: 0.2593, Adjusted R-squared: 0.2584
## F-statistic: 286 on 1 and 817 DF, p-value: < 2.2e-16
## Slope SE Slope P Slope Intercept SE int.
## flux_W92_ano 4.745219e-06 1.087736e-06 1.489053e-05 -0.009564072 0.002192355
## flux_W14_ano 4.814507e-06 1.167391e-06 4.189495e-05 -0.009703724 0.002352901
## P int. F df R2 P value
## flux_W92_ano 1.489102e-05 19.03116 669 0.02766032 1.489053e-05
## flux_W14_ano 4.189620e-05 17.00869 669 0.02479369 4.189495e-05
## tau slope intercept
## 1.527953e-01 1.568705e-06 -2.526831e-03
by Wanninkhof et al. (2014) method :
Increase of CO2 fluxes (more and more sources)
→ remove seasonality : bug dans les data
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_flux_2014_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.488e-04 -3.568e-05 7.000e-07 3.192e-05 1.557e-03
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.034e-03 1.814e-03 -2.223 0.0265 *
## x 2.012e-06 9.006e-07 2.234 0.0258 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0001089 on 778 degrees of freedom
## Multiple R-squared: 0.006372, Adjusted R-squared: 0.005095
## F-statistic: 4.989 on 1 and 778 DF, p-value: 0.02579
## mapping: x = ~x, y = ~y
## geom_text: na.rm = FALSE
## stat_identity: na.rm = FALSE
## position_identity
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_sal_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.26888 -0.07384 0.05299 0.16776 0.43462
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.815e+01 4.277e+00 8.918 <2e-16 ***
## x -9.817e-05 2.123e-03 -0.046 0.963
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2828 on 830 degrees of freedom
## Multiple R-squared: 2.577e-06, Adjusted R-squared: -0.001202
## F-statistic: 0.002139 on 1 and 830 DF, p-value: 0.9631
## tau slope intercept
## 0.08353456 0.00490000 28.60030667
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pH_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.076080 -0.012476 0.000513 0.011960 0.060379
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16.0024176 0.3081464 51.93 <2e-16 ***
## x -0.0039360 0.0001529 -25.74 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0199 on 817 degrees of freedom
## Multiple R-squared: 0.4477, Adjusted R-squared: 0.4471
## F-statistic: 662.3 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## -0.507330174 -0.003704364 14.971413986
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pH_18_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.060691 -0.009506 0.000687 0.009573 0.065294
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14.3268199 0.2375706 60.31 <2e-16 ***
## x -0.0030983 0.0001179 -26.28 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01534 on 817 degrees of freedom
## Multiple R-squared: 0.458, Adjusted R-squared: 0.4574
## F-statistic: 690.5 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## -0.518178316 -0.003066204 14.369182200
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_ta_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -54.183 -7.254 0.808 8.163 30.760
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.429e+03 1.945e+02 7.351 4.80e-13 ***
## x 5.588e-01 9.651e-02 5.790 1.01e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12.56 on 817 degrees of freedom
## Multiple R-squared: 0.03941, Adjusted R-squared: 0.03824
## F-statistic: 33.52 on 1 and 817 DF, p-value: 1.006e-08
## tau slope intercept
## 0.1524274 0.6902784 997.1132050
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_dic_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -60.17 -14.03 -0.83 14.51 55.79
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2521.6374 302.5181 -8.335 3.25e-16 ***
## x 2.3672 0.1501 15.766 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 19.54 on 817 degrees of freedom
## Multiple R-squared: 0.2333, Adjusted R-squared: 0.2323
## F-statistic: 248.6 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## 0.4775709 2.4504033 -2706.5094691
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2w_less_season)
##
## Residuals:
## Min 1Q Median 3Q Max
## -107.13 -46.92 -22.05 44.40 177.38
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.003e+04 9.222e+02 -10.88 <2e-16 ***
## x 5.181e+00 4.577e-01 11.32 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 59.55 on 817 degrees of freedom
## Multiple R-squared: 0.1356, Adjusted R-squared: 0.1345
## F-statistic: 128.1 on 1 and 817 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_temp_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.2775 -0.5134 -0.0880 0.4173 6.0455
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -37.313483 14.961975 -2.494 0.012829 *
## x 0.026215 0.007425 3.531 0.000438 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9892 on 830 degrees of freedom
## Multiple R-squared: 0.0148, Adjusted R-squared: 0.01361
## F-statistic: 12.46 on 1 and 830 DF, p-value: 0.0004376
## tau slope intercept
## 0.1110322 0.0243000 -37.2137708
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_sal_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.47554 -0.06860 0.00289 0.07377 0.61930
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.774390 1.652383 11.36 <2e-16 ***
## x 0.009572 0.000820 11.67 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1093 on 830 degrees of freedom
## Multiple R-squared: 0.141, Adjusted R-squared: 0.14
## F-statistic: 136.3 on 1 and 830 DF, p-value: < 2.2e-16
## tau slope intercept
## 0.2750824 0.0100000 16.8464417
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pH_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.081794 -0.008057 0.000551 0.008147 0.114830
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14.7900219 0.2511412 58.89 <2e-16 ***
## x -0.0033168 0.0001246 -26.61 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01622 on 817 degrees of freedom
## Multiple R-squared: 0.4643, Adjusted R-squared: 0.4636
## F-statistic: 708.1 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## -0.548754417 -0.003420801 15.015599410
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pH_18_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.072582 -0.010171 0.000697 0.010221 0.121933
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14.0332562 0.2826450 49.65 <2e-16 ***
## x -0.0029604 0.0001403 -21.10 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01825 on 817 degrees of freedom
## Multiple R-squared: 0.3528, Adjusted R-squared: 0.352
## F-statistic: 445.4 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## -0.470840610 -0.002894506 13.802968602
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_ta_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -38.215 -6.571 -0.937 7.815 29.959
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.373e+03 1.614e+02 8.504 < 2e-16 ***
## x 5.863e-01 8.012e-02 7.318 6.03e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.43 on 817 degrees of freedom
## Multiple R-squared: 0.06151, Adjusted R-squared: 0.06037
## F-statistic: 53.55 on 1 and 817 DF, p-value: 6.029e-13
## tau slope intercept
## 0.1965052 0.7572943 1064.3597858
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_dic_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -64.95 -12.28 0.03 11.52 54.00
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2272.570 274.103 -8.291 4.6e-16 ***
## x 2.247 0.136 16.517 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 17.7 on 817 degrees of freedom
## Multiple R-squared: 0.2503, Adjusted R-squared: 0.2494
## F-statistic: 272.8 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## 0.450883 2.380600 -2850.367607
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_pco2w_less_season_50)
##
## Residuals:
## Min 1Q Median 3Q Max
## -84.922 -11.031 -0.924 9.265 98.287
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6628.9443 282.2897 -23.48 <2e-16 ***
## x 3.4725 0.1401 24.79 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 18.23 on 817 degrees of freedom
## Multiple R-squared: 0.4292, Adjusted R-squared: 0.4285
## F-statistic: 614.3 on 1 and 817 DF, p-value: < 2.2e-16
## tau slope intercept
## 0.5533502 3.4851246 -6955.6345671
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_temp_less_season_9522_surf)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.9571 -3.6091 -0.6303 3.5240 9.8422
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -49.75311 27.24729 -1.826 0.0681 .
## x 0.03402 0.01356 2.508 0.0122 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.183 on 1454 degrees of freedom
## Multiple R-squared: 0.004308, Adjusted R-squared: 0.003623
## F-statistic: 6.29 on 1 and 1454 DF, p-value: 0.01225
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_sal_less_season_9522_surf)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.42274 -0.13985 0.05868 0.18375 0.54799
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 40.5588102 1.8779517 21.597 <2e-16 ***
## x -0.0012956 0.0009348 -1.386 0.166
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2883 on 1454 degrees of freedom
## Multiple R-squared: 0.00132, Adjusted R-squared: 0.0006327
## F-statistic: 1.921 on 1 and 1454 DF, p-value: 0.1659
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_temp_less_season_9522_prof)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.6229 -1.1545 -0.2938 0.6839 8.7835
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13.516602 11.013142 -1.227 0.2199
## x 0.014359 0.005482 2.619 0.0089 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.691 on 1454 degrees of freedom
## Multiple R-squared: 0.004696, Adjusted R-squared: 0.004012
## F-statistic: 6.861 on 1 and 1454 DF, p-value: 0.008903
##
## Call:
## lm(formula = y ~ x, data = reg_val_ts_sal_less_season_9522_prof)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.46253 -0.08635 0.01237 0.08505 0.62809
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 32.849724 0.976407 33.643 < 2e-16 ***
## x 0.002587 0.000486 5.323 1.18e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1499 on 1454 degrees of freedom
## Multiple R-squared: 0.01912, Adjusted R-squared: 0.01844
## F-statistic: 28.34 on 1 and 1454 DF, p-value: 1.18e-07
For temperature and pCO2 seawater at Point B (2007-2022)
## Months pco2_slope temp_slope pCO2_therm_slope pCO2_nontherm_slope
## 1 Jan 2.523016 0.0332857143 0.3530380 2.599444
## 2 Fev 3.291239 0.0175500000 0.4688629 3.595500
## 3 Mar 2.988714 0.0135263158 0.2052708 3.043133
## 4 Avr 3.775814 0.0349500000 -0.1324544 4.787059
## 5 Mai 4.112468 0.0002857143 -0.7590820 5.218764
## 6 Juin 7.667212 0.0422291667 2.4934047 4.366127
## 7 Juil 9.053771 0.0896754386 4.5094011 3.810839
## 8 Août 7.599453 0.0657434211 4.0177563 3.281861
## 9 Sept 4.000817 0.0594166667 1.7602493 2.084349
## 10 Oct 3.518555 0.0231666667 0.5950417 3.016746
## 11 Nov 4.231577 0.0375714286 1.0756394 3.381699
## 12 Dec 3.236259 0.0496260870 0.7331855 2.829150